An original signal processing algorithm is presented to automatically extract, on a stride-by-stride basis, four consecutive fundamental events of walking, heel strike (HS), toe strike (TS), heel-off (HO), and toe-off (TO), from wireless accelerometers applied to the right and left foot. First, the signals recorded from heel and toe three-axis accelerometers are segmented providing heel and toe flat phases. Then, the four gait events are defined from these flat phases. The accelerometer-based event identification was validated in seven healthy volunteers and a total of 247 trials against reference data provided by a force plate, a kinematic 3D analysis system, and video camera. HS, TS, HO, and TO were detected with a temporal accuracy ± precision of 1.3 ms ± 7.2 ms, ‒4.2 ms ± 10.9 ms, ‒3.7 ms ± 14.5 ms, and ‒1.8 ms ± 11.8 ms, respectively, with the associated 95% confidence intervals ranging from ‒6.3 ms to 2.2 ms. It is concluded that the developed accelerometer-based method can accurately and precisely detect HS, TS, HO, and TO, and could thus be used for the ambulatory monitoring of gait features computed from these events when measured concurrently in both feet. [less ▲]

Researchers rarely provide solid performance and validation information about their acceleometer-based approaches to human gait analysis. We present here a novel signal processing and analysis algorithm that automatically extracts four consecutive fundamental events of walking: heel strike (HS), toe strike (TS), heel off (HO), and toe off (TO). In addition, we validate this accelerometer-based technique by comparing these extracted gait events with those obtained by a kinematic 3D analysis system and a force plate, used as gold standards. [less ▲]

in IEEE International Conference on 3D Imaging (IC3D) (2012, December)

This work is part of a project that deals with the three-dimensional (3D) analysis of normal and pathological gaits based on a newly developed system for clinical applications, using low-cost wireless ... [more ▼]

This work is part of a project that deals with the three-dimensional (3D) analysis of normal and pathological gaits based on a newly developed system for clinical applications, using low-cost wireless accelerometers and a signal processing algorithm. This system automatically extracts relevant gait events such as the heel strikes (HS) and the toe-offs (TO), which characterize the stance and the swing phases of walking. The performances of the low-cost accelerometer hardware and related algorithm have been compared to those obtained by a kinematic 3D analysis system and a force plate, used as gold standard methods. The HS and TO times obtained from the gait data of 7 healthy volunteers (147 trials) have been found to be (mean ± standard deviation) 0.42±7.92 ms and 3.11±10.08 ms later than those determined by the force plate, respectively. The experimental results demonstrate that the new hardware and associated algorithm constitute an effective low-cost gait analysis system, which could thus be used for the assessment of mobility in routine clinical practice. [less ▲]

Introduction: Brisk walking (BW) is an efficient tool to study gait hypokinesia whose pathogenesis remains poorly understood in Parkinson's disease (PD). Aims: Assuming that brain regions recruited during imagined gait strongly overlap with those recruited during real gait, we used mental imagery of BW as a paradigm to study the neural correlates of gait hypokinesia in PD with BOLD fMRI. Methods: 15 'on-drugs' PD patients and 15 controls matched for age and gender were instructed to imagine themselves in two situations: comfortable walking (CW) and BW on a 25 meter-path. Imagined speed reserve (ISR), defined as the difference between imagined BW and CW speeds, was measured as a control of behavioral performance. The first-level individual contrast images representing the comparison between BW and CW were entered into second-level analyses with the corresponding ISRs as correlation regressors. Results: ISRs and their real counterparts measured offline were significantly decreased in patients relatively to controls. They strongly positively correlated in patients (Pearson's r = 0.88) and controls (Pearson's r = 0.59). Between-group comparison of individual contrasts BW minus CW in correlation with their corresponding ISRs showed that increasing imagined gait speed was strongly associated with increased activity of the left posterior parietal cortex (PPC) in controls and with decreased activity of this region in the patients. Conclusions: Our findings suggest that gait hypokinesia is related to an impaired function of the left PPC in PD. The left PPC may represent a target for therapeutic interventions aimed at alleviating gait disturbances in PD. [less ▲]

Gait disturbances represent a therapeutic challenge in Parkinson's disease (PD). To further investigate their underlying pathophysiological mechanisms, we compared brain activation related to mental imagery of gait between 15 PD patients and 15 age-matched controls using a block-design functional MRI experiment. On average, patients showed altered locomotion relatively to controls, as assessed with a standardized gait test that evaluated the severity of PD-related gait disturbances on a 25-m path. The experiment was conducted in the subjects as they rehearsed themselves walking on the same path with a gait pattern similar as that during locomotor evaluation. Imagined walking times were measured on a trial-by-trial basis as a control of behavioral performance. In both groups, mean imagined walking time was not significantly different from that measured during real gait on the path used for evaluation. The between-group comparison of the mental gait activation pattern with reference to mental imagery of standing showed hypoactivations within parieto-occipital regions, along with the left hippocampus, midline/lateral cerebellum, and presumed pedunculopontine nucleus/mesencephalic locomotor area, in patients. More specifically, the activation level of the right posterior parietal cortex located within the impaired gait-related cognitive network decreased proportionally with the severity of gait disturbances scored on the path used for gait evaluation and mental imagery. These novel findings suggest that the right posterior parietal cortex dysfunction is strongly related to the severity of gait disturbances in PD. This region may represent a target for the development of therapeutic interventions for PD-related gait disturbances. (c) 2012 Movement Disorder Society. [less ▲]

Objective: To investigate the neural correlates of hypokinetic gait in Parkinson’s disease (PD) using functional magnetic resonance imaging (fMRI). Background: Although hypokinetic gait is frequent and has a negative impact on quality of life in PD, its underlying mechanisms remain poorly understood. Assuming that the brain regions recruited during real and imagined gait strongly overlap, mental imagery of brisk gait may be a successful approach to study hypokinetic gait in PD. Methods: Fifteen ‘‘on-drugs’’ PD patients (8 males; mean age 5 65.1 6 9.4 years) and fifteen controls matched for age, gender and mental imagery skills were trained to perform video-taped trials of comfortable and brisk gait on a 25 meter-path. The study was organ- ized as a block-design fMRI experiment where subjects were instructed to rehearse themselves performing comfortable and brisk gait and to press a key to indicate when they completed each 25 meter-imagined gait trial. The imagined speed reserve (ISR) defined as the difference between imagined brisk and comfortable gait speeds was measured as a control of behavioral performance. Imaging data processing and analyses were performed using SPM8. The first-level individual contrast images representing the comparison between brisk and comfortable gait were entered as two separate groups (controls vs patients) in an ANOVA with the corresponding ISRs as correlation regressors. Results: Compared with controls, patients showed hypokinetic gait during real gait training as their increase in speed during brisk relatively to comfortable gait was related to an increase in step ca- dence (r50.87; p<0.001) but not in step length (r50.11). ISRs meas- ured during fMRI and their real counterparts measured offline strongly correlated in patients (r50.88; p<0.001) and controls (r50.59; p50.02). Between-group comparison (p<0.001, uncorrected) of fMRI data showed that increasing imagined gait speed was strongly associated with increased activity of the left posterior parietal cortex in controls and with decreased activity of this region in patients. Conclusions: Our findings suggest that hypokinetic gait in PD is related to the impaired functioning of the left posterior parietal cortex. This area may represent a target for therapeutic interventions aimed at alleviating gait disturbances in PD. [less ▲]

The clinical hallmarks of Parkinson’s disease (PD) are movement poverty and slowness (i.e. bradykinesia), muscle rigidity, limb tremor or gait disturbances. Parkinson’s gait include slowness, shuffling, short steps, freezing of gait (FoG) and/or asymmetries in gait. There are currently no validated clinical instruments or device that allow a full characterization of gait disturbances in PD. As a step towards this goal, a four accelerometer-based system is proposed to increase the number of parameters that can be extracted to characterize parkinsonian gait disturbances such as FoG or gait asymmetries. After developing the hardware, an algorithm has been developed, that automatically epoched the signals on a stride-by-stride basis and quantified, among others, the gait velocity, the stride time,the stance and swing phases, the single and double support phases or the maximum acceleration at toe-off, as validated by visual inspection of video recordings during the task. The results obtained in a PD patient and an healthy volunteer are presented. The FoG detection will be improved using time-frequency analysis and the system is about to be validated with a state-of-the-art 3D movement analysis system. [less ▲]

in Proceedings 10th IEEE International Conference on Information Technology and Applications in Biomedicine (ITAB 2010) (2010)

The clinical hallmarks of Parkinson's disease (PD) are movement poverty and slowness (i.e. bradykinesia), muscle rigidity and limb tremor. The physicians usually quantify these motor disturbances by ... [more ▼]

The clinical hallmarks of Parkinson's disease (PD) are movement poverty and slowness (i.e. bradykinesia), muscle rigidity and limb tremor. The physicians usually quantify these motor disturbances by assigning a severity score according to validated but time-consuming clinical scales such as the Unified Parkinson's Disease Rating Scale (UPDRS) - part III. These clinical ratings are however prone to subjectivity and inter-rater variability. The PD medical community is therefore looking for a faster and more objective rating method. As a first step towards this goal, a tri-axial accelerometer-based system is proposed as patients are engaged in a repetitive finger tapping task, which is classically used to assess bradykinesia in the UPDRS-III. After developing the hardware, an algorithm has been developed, that automatically epoched the signal on a trial-by-trial basis and quantified, among others, movement speed, amplitude, hesitations or halts as validated by visual inspection of video recordings during the task. The results obtained in a PD patient and an healthy volunteer are presented. Preliminary results show that PD patients and healthy volunteers have different features profiles, so that a classifier could be set up to predict objective UPDRS-III scores. [less ▲]